A conventional positioning system for a robot includes a Global Positioning System (GPS), an Inertial Navigation System (INS) or etc. The GPS has advantages of wide usage range and high accuracy, but is mostly affected by environment. The INS is capable of being independently in operation and has high frequency, but is mostly affected by noise signals. In recent years, one of most common methods for navigating the robot is to combine the GPS and INS, which may effectively use their respective advantages and complement each other. However, in practical implementation, a GPS signal may be prevented from being received by an obstruction in many cases, so that a positioning accuracy of the whole system is significantly reduced.
Therefore, people are looking for reliable positioning methods to take the place of the GPS, one of which is the visual navigation method. In such method, a movement of a vehicle is estimated by determining positions of the vehicle in a three-dimensional (3D) space based on matching of characteristic points in neighboring image frames, which overcomes the defects in the conventional positioning method and gains more and more attention as an effective complement of the conventional positioning method. Meanwhile, the visual navigation method is also required to be improved.
The conventional visual navigation method is implemented based on a binocular stereo camera and is of a high positioning accuracy. However, such method has disadvantages such as being difficult to be calibrated and suppress an error. Furthermore, since the binocular stereo camera has two lenses for capturing images, an amount of data being gathered is larger than before, and a processing speed is hard to be controlled, so that such method is poor in real-time processing.
As a result, it is desired to propose a visual navigation method or device which is good in real-time processing, easy to be controlled and of high accuracy, so as to meet higher demand in the field.